Networks, in particular mobile networks, are looking for significant gains in terms of capacity, reliability, energy consumption, etc. The transmission channel of a mobile network has the reputation of being difficult and leads to relatively mediocre transmission reliability. Significant progress has been achieved in recent years in terms of coding and modulation, in particular for energy consumption considerations and capacity considerations. In a mobile network where a plurality of transceivers share the same resources (time, frequency, and space), it is necessary to keep transmission power as low as possible.
Such low power goes against coverage and thus against the capacity of the system, and more generally against its performance.
In order to increase coverage, to make communications more reliable, and more generally to improve performance, one approach consists in relying on relays for increasing spectrum efficiency and thus for improving the transmission efficiency and the reliability of systems. The topology of MARC systems as shown in FIG. 1 is such that the sources, nodes S1 and S2, broadcast their coded information sequences for the attention of the relay R and of the destination D. The relay decodes the signals it receives from the sources S1 and S2 and it re-encodes them jointly while adding its own redundancy so as to create a spatially-distributed network code. At the destination D, the decoding of the three spatially-distributed coded sequences, comprising two coded sequences received directly from the sources S1 and S2 and the coded sequence coming from the relay, relies on joint channel/network decoding algorithms.
Network coding is a form of co-operation in which the nodes of the network share not only their own resources (power, band, etc.) but also their calculation capacity, so as to create distributed coding of power that increases with continuing propagation of information through the nodes. It provides substantial improvements in terms of diversity and of coding, and thus of transmission reliability.
Two types of operation are known for the relay: half-duplex mode and full-duplex mode.
In half-duplex mode, there are two transmission stages that correspond to different time slots since the relay is not capable of receiving and transmitting simultaneously. During the first stage that comprises the first time slots (also referred to as transmission intervals), both of the sources transmit but not the relay. The relay decodes and re-encodes jointly in order to deduce the signal it is to transmit during the following time slots. During the second stage that comprises the second time slots, the relay transmits the signal it determined during the first time slots, and the sources transmit the parity second sequences relating to the same information as the information transmitted during the first time slots. Half-duplex type relays are attractive because of a communications scheme that is simple and because of the ease with which they can be implemented and the low cost that stems therefrom.
In full-duplex mode, the relay receives the new information blocks from the two sources and it transmits simultaneously to the destination its own code word based on blocks it has received beforehand. Compared with a half-duplex relay, a full-duplex relay makes it possible to achieve greater capacity.
Articles [1] and [2] describe joint channel/network coding for a MARC system, as shown in FIG. 2. The MARC system under consideration is such that the links CH14, CH24, CH13, CH43, and CH23 are orthogonal, and in addition the links between the two sources and the relay are assumed to be completely reliable. In that application, a link is a communications channel between two or more nodes, and it may be physical or logical. When the link is physical, then it is generally referred to as a “channel”. The two sources S1 and S2 broadcast the coded information to the relay R and to the destination D during the first transmission stage. The relay R takes the streams that it is assumed to have decoded perfectly from the two users, and it combines them in linear manner by using a linear network coding scheme. During the second stage, the relay transmits an additional parity sequence to the destination D. Once all of the streams have been received, stored, and reorganized by the destination, this joint channel/network code may be considered as a spatially-distributed joint channel/network code that may be decoded iteratively. This joint code leads to substantial gains in terms of diversity and coding.
S. Yang and R. Koetter [3] have evaluated the performance of network coding for a MARC system, as shown in FIG. 3, with orthogonal links, but in the presence of source-relay links that are noisy. The authors propose the soft decode-and-forward technique that relies on generating a discrete probability distribution for the bits that are to be transmitted, as obtained by an algorithm that calculates a posteriori probabilities (APP) for the coded bits/symbols. Each source S1, S2 generates a code word that is transmitted to the relay R. The relay R decodes them in the form of a logarithmic likelihood ratio (LLR) using a BCJR decoding algorithm, named after its authors L. Bahl, J. Cocke, F. Jelinek, and J. Raviv [4], and then performs memoryless weighted network coding corresponding to the bitwise modulo two sum (XOR operation) of the two received code words, the weighted coding consisting in using the LLRs L1, L2 of the two sources to generate a third LLR LR corresponding to the XOR operation. Finally, this third LLR is transmitted in analog form to the destination D. Thus, the destination has three observations: those coming from the two sources and that from the LLR. The destination performs joint and iterative decoding of the streams from the sources S1 and S2 while making use of the additional information provided by the relay. The article states that even with S1→R and S2→R links that are severely noisy, the network coding provides a coding improvement compared with a scheme without co-operation, and thus without a relay. The method is described when using binary phase shift keying (BPSK) and it cannot be transposed to modulation of an order greater than two since the expression calculated during the third step is applicable only to modulation of order two or of order four (e.g. quadrature phase shift keying (QPSK)).
In those various known systems, decoding errors are reduced solely in the absence of interference, since the MARC system under consideration is assumed to be without interference as a result of the orthogonal links. Furthermore, the constraint that consists in imposing orthogonal links leads to non-optimum utilization of the spectrum resource and thus to a limit on the capacity of the network.